Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper considers testing for structural change in long-memory time series. We modify the Wilcoxon two-sample rank test by standardizing it with a kernel-based fixed bandwidth long-run variance estimator. The corresponding test statistic converges to a well-defined distribution under the null hypothesis. In a Monte Carlo simulation we confirm that the test provides good finite sample size and power results and compare it with an existing approach.